Fuzzy-based positioning for mobile robots

This paper proposes fuzzy-based positioning algorithms for an iRobot B21r mobile robot, which is equipped with a 180° scanning laser rangefinder and other sensors, in an indoor environment. A novel, dynamic error model for the laser rangefinder is built with consideration of the detection distance and the detection angle. A new concept, the virtual angular point, is introduced in this paper as one of the features for positioning a mobile robot. To position a mobile robot, three kinds of feature points, such as break points, real angular points, and virtual angular points, are employed in this paper. Based on fuzzy evaluation for the accuracy of each feature point, positions obtained by two arbitrary points are fused together by the weighted mean technique, in which weight is determined by the uncertainty represented by fuzzy numbers. Experimental study has been carried out to verify the effectiveness and the accuracy of the algorithms.